Enhanced Dynamic Clinical Decision Support System Pragmatic Trial (E-DYNAMIC)

NCT03826758 | Unknown DMC

• 1 other identifier: 211972
• Study Type: interventional
• Target: 8,000
• Locations: 1 country
• Sites: 1

Brief Summary

Chronic kidney disease (CKD) is a highly prevalent, poorly recognized and undertreated and increases risk of atherosclerotic cardiovascular disease (ASCVD) and mortality. ASCVD risk interventions such as statin medications are not effective if initiated when kidney disease is advanced. Thus, early recognition of CKD is important for effective ASCVD risk management. Patient centered medical homes (PCMH)s (clinics which include nurse educators, dietitians, pharmacists and social workers) were designed to address gaps in care for complex chronic diseases such as CKD by increasing availability of ancillary services for patients. However, PCMH models have not been shown to improve the recognition and treatment of CKD and its associated ASCVD risk. The E DYNAMIC CDS retrieves real-time patient data from the electronic health record (EHR) every 24 hours to help primary care providers (PCP) identify patients with CKD and assess ASCVD risk and provide appropriate treatment. E-DYNAMIC also delegates CKD care with utilization of an opt-out approach for nurse education and dietitian referral. The overall objective of this pragmatic trial is to examine whether the E-DYNAMIC CDS increases PCP recognition of CKD and use of ASCVD risk management interventions when implemented within a PCMH. This pragmatic trial will be conducted within the Hines VA Hospital and community-based outpatient clinics designed as PCMH called teamlets. Teamlets include several PCPs, a nurse educator, a dietitian, a pharmacist, and a social worker. We will randomize 51 teamlets to the E-DYNAMIC CDS or to standard care. This pragmatic trial will address the following aims: 1) Determine the difference in PCP diagnosis of CKD stage 3-5 non-dialysis dependent CKD by allocation to the E-DYNAMIC CDS; 2) Determine the difference in PCPs ASCVD risk management of patients with stage 3-5 non-dialysis dependent CKD by teamlet allocation to the E-DYNAMIC CDS; 3) Determine the difference in patient use of ASCVD risk interventions and patient activation measures by their teamlet allocation to the E-DYNAMIC CDS. The primary outcomes of the pragmatic trial will be ascertained from the EHR. The E-DYNAMIC CDS tool may be transferred into other health systems that utilize an EHR and improve the diagnosis and management of CKD.

Conditions

Chronic Kidney Diseases

Keywords

chronic kidney disease; clinical decision support; health informatics; pragmatic clinical trial

Outcome Measures

Primary Outcomes (3)

• Proportion of a primary care providers' patients with chronic kidney disease (CKD) with clinically recognized chronic kidney disease (CKD).

  We define CKD as two estimated glomerular filtration rate (eGFR) values \< 60 spaced ≥90 days apart with no intervening eGFR values ≥ 60 ml/min/1.73 m2 based on outpatient laboratory values within 18 months of the index primary care visit. Using administrative data, we will determine the proportion of a primary care providers' patients with CKD who have clinically recognized CKD defined as presence of a ICD9/10 billing code for CKD in the administrative records or mention of CKD in the problem list. The outcome variable is binary and categorized as recognized vs. not recognized CKD.

  12 months follow-up after the index primary care visit

• Proportion of a primary care providers' patients with CKD prescribed at least two of the atherosclerotic cardiovascular disease- (ASCVD) CKD care metrics.

  Using administrative data, we will determine the proportion of a primary care providers' patients with CKD who are prescribed at least two of the ASCVD-CKD care metrics over a 12 month period: 1) Urine albumin level, including up to 1 month before the index primary care visit, 2) Documentation of nurse education. 3) Medical nutrition therapy with a registered dietitian. 4) Statin prescription (new or renewal of existing prescription), 5) Angiotensin Converting Enzyme Inhibitor or Angiotensin Receptor Blocker (ACE/ARB) prescription (new or renewal) for patient with clinic blood pressure ≥ 130/80mm Hg or ICD9/10 code for hypertension in the 6 months before the index primary care visit, 6) Referral to nephrology for CKD stage 4-5 (eGFR \< 30 ml/min/1.73 m2). The outcome variable is binary and defined as being prescribed at least two ASCVD-CKD care metrics versus \< 2 ASCVD-CKD care metrics.

  12 months follow-up after the index primary care visit

• Proportion of patients who utilize at least two of the ASCVD-CKD care interventions.

  Using administrative data, we will determine the proportion of patients with CKD who used ASCVD-CKD care interventions. ASCVD-CKD care interventions include: 1) Documentation of nurse education. 2) Documentation of medical nutrition therapy with a registered dietitian. 3) Statin prescription (new or renewal of existing prescription) with proportion of days covered ≥ 80%, 4) Angiotensin Converting Enzyme Inhibitor or Angiotensin Receptor Blocker (ACE/ARB) prescription (new or renewal) with proportion of days covered ≥ 80% (for patient with clinic blood pressure ≥ 130/80mm Hg or ICD9/10 code for hypertension in the 6 months before the index primary care visit), 5) Referral to nephrology for CKD stage 4-5 (eGFR \< 30 ml/min/1.73 m2). The outcome variable is binary and defined as being prescribed at least two ASCVD-CKD care metrics versus \< 2 ASCVD-CKD care metrics.

  12 months follow-up after the index primary care visit

Secondary Outcomes (2)

• Patient activation

  One month before and 6 months after the index primary care visit

• Proportion of patients who used ancillary care

  12 months follow-up after the index primary care visit

Study Arms (2)

E-DYNAMIC CDS

OTHER

E-DYNAMIC clinical decision support (CDS) retrieves near-real time patient data from the electronic health record to help primary care providers identify patients with stage 3-5 CKD, present ASCVD risk, statin use and clinical recommendations for ASCVD risk reduction at point of care. E-DYNAMIC directs referrals to nurses for CKD education and to dietitians for MNT. Providers are also nudged to prescribe statin medications and address hypertension management.

Other: E-DYNAMIC Clinical Decision Support

Standard care

NO INTERVENTION

No change in their clinical practice.

Interventions

E-DYNAMIC Clinical Decision Support OTHER

Clinical decision support system

E-DYNAMIC CDS

Eligibility Criteria

• Age: 50 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• All patients with chronic kidney disease (50 years and older, non-dialysis dependent and who had not received kidney transplant) seen by the primary care providers during the study period will be included in this study.
• Practicing primary provider at any of the Edward Hines Jr. hospital outpatient clinics or community based outpatient clinics
• Willing to be involved in the E-DYNAMIC clinical trial

You may not qualify if:

• \- Provider not willing to be involved in the E-DYNAMIC clinical trial

Sponsors & Collaborators

• Loyola University: lead

Study Sites (1)

Edward Hines Jr. Hospital and associated Community Outpatient Based Clinics

Hines, Illinois, 60141, United States

Location

Related Publications (8)

• Saran R, Robinson B, Abbott KC, Agodoa LY, Albertus P, Ayanian J, Balkrishnan R, Bragg-Gresham J, Cao J, Chen JL, Cope E, Dharmarajan S, Dietrich X, Eckard A, Eggers PW, Gaber C, Gillen D, Gipson D, Gu H, Hailpern SM, Hall YN, Han Y, He K, Hebert H, Helmuth M, Herman W, Heung M, Hutton D, Jacobsen SJ, Ji N, Jin Y, Kalantar-Zadeh K, Kapke A, Katz R, Kovesdy CP, Kurtz V, Lavalee D, Li Y, Lu Y, McCullough K, Molnar MZ, Montez-Rath M, Morgenstern H, Mu Q, Mukhopadhyay P, Nallamothu B, Nguyen DV, Norris KC, O'Hare AM, Obi Y, Pearson J, Pisoni R, Plattner B, Port FK, Potukuchi P, Rao P, Ratkowiak K, Ravel V, Ray D, Rhee CM, Schaubel DE, Selewski DT, Shaw S, Shi J, Shieu M, Sim JJ, Song P, Soohoo M, Steffick D, Streja E, Tamura MK, Tentori F, Tilea A, Tong L, Turf M, Wang D, Wang M, Woodside K, Wyncott A, Xin X, Zang W, Zepel L, Zhang S, Zho H, Hirth RA, Shahinian V. US Renal Data System 2016 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis. 2017 Mar;69(3 Suppl 1):A7-A8. doi: 10.1053/j.ajkd.2016.12.004. No abstract available.

  PMID: 28236831 BACKGROUND

• Matsushita K, Coresh J, Sang Y, Chalmers J, Fox C, Guallar E, Jafar T, Jassal SK, Landman GW, Muntner P, Roderick P, Sairenchi T, Schottker B, Shankar A, Shlipak M, Tonelli M, Townend J, van Zuilen A, Yamagishi K, Yamashita K, Gansevoort R, Sarnak M, Warnock DG, Woodward M, Arnlov J; CKD Prognosis Consortium. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. Lancet Diabetes Endocrinol. 2015 Jul;3(7):514-25. doi: 10.1016/S2213-8587(15)00040-6. Epub 2015 May 28.

  PMID: 26028594 BACKGROUND

• Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH. Longitudinal follow-up and outcomes among a population with chronic kidney disease in a large managed care organization. Arch Intern Med. 2004 Mar 22;164(6):659-63. doi: 10.1001/archinte.164.6.659.

  PMID: 15037495 BACKGROUND

• Plantinga LC, Boulware LE, Coresh J, Stevens LA, Miller ER 3rd, Saran R, Messer KL, Levey AS, Powe NR. Patient awareness of chronic kidney disease: trends and predictors. Arch Intern Med. 2008 Nov 10;168(20):2268-75. doi: 10.1001/archinte.168.20.2268.

  PMID: 19001205 BACKGROUND

• Palmer SC, Navaneethan SD, Craig JC, Johnson DW, Perkovic V, Hegbrant J, Strippoli GF. HMG CoA reductase inhibitors (statins) for people with chronic kidney disease not requiring dialysis. Cochrane Database Syst Rev. 2014 May 31;(5):CD007784. doi: 10.1002/14651858.CD007784.pub2.

  PMID: 24880031 BACKGROUND

• Prabhakaran D, Jha D, Prieto-Merino D, Roy A, Singh K, Ajay VS, Jindal D, Gupta P, Kondal D, Goenka S, Jacob P, Singh R, Kumar BGP, Perel P, Tandon N, Patel V; Members of the Research Steering Committee,Investigators,Members of the Data Safety and Monitoring Board. Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial. Circulation. 2019 Jan 15;139(3):380-391. doi: 10.1161/CIRCULATIONAHA.118.038192. Epub 2018 Nov 10.

  PMID: 30586732 BACKGROUND

• Sinaiko AD, Landrum MB, Meyers DJ, Alidina S, Maeng DD, Friedberg MW, Kern LM, Edwards AM, Flieger SP, Houck PR, Peele P, Reid RJ, McGraves-Lloyd K, Finison K, Rosenthal MB. Synthesis Of Research On Patient-Centered Medical Homes Brings Systematic Differences Into Relief. Health Aff (Millwood). 2017 Mar 1;36(3):500-508. doi: 10.1377/hlthaff.2016.1235.

  PMID: 28264952 BACKGROUND

• Hibbard JH, Stockard J, Mahoney ER, Tusler M. Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res. 2004 Aug;39(4 Pt 1):1005-26. doi: 10.1111/j.1475-6773.2004.00269.x.

  PMID: 15230939 BACKGROUND

MeSH Terms

Conditions

Renal Insufficiency, Chronic

Condition Hierarchy (Ancestors)

Renal Insufficiency; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Holly J Mattix-Kramer, MD MPH

  Loyola University Chicago

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Holly J Mattix-Kramer, MD MPH

CONTACT

7083279039; hkramer@lumc.edu

Talar Markossian, PhD

CONTACT

7083279027; tmarkossian@luc.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Model Details: Pragmatic randomized clinical parallel trial with two arms

Study Record Dates

• First Submitted: January 30, 2019
• First Posted: February 1, 2019
• Study Start: January 1, 2021
• Primary Completion: October 1, 2021
• Study Completion: September 30, 2023
• Last Updated: August 27, 2020

Record last verified: 2020-08

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR
• Time Frame: The website will be built once funding has been secured for the trial. The study protocol and consent and the E-DYNAMIC clinical decision support tool will be available on the web-site once the web-site is built. Funding is anticipated by October of 2019. Results of the clinical trial will be posted after publication of the main results. This is anticipated in October of 2022.
• Access Criteria: Access will be by publicly available website

Locations

US (1)